Abstract
BACKGROUND: Artificial intelligence (AI) tools such as ChatGPT are increasingly applied in digital health and patient education, yet their alignment with established clinical guidelines for cancer-related nutritional management remains unclear. OBJECTIVE: This study aimed to evaluate the concordance, functional characteristics, patient accessibility, and innovation of ChatGPT-generated nutritional recommendations compared with clinical guidelines from the Chinese Society of Clinical Oncology (CSCO), Chinese Nutrition Society (CNS), and European Society for Clinical Nutrition and Metabolism (ESPEN). METHODS: We analyzed ChatGPT responses across six key nutrition-related issues—anorexia/cachexia, dysphagia, oral mucositis, unintentional weight loss, gastrointestinal intolerance, and nutritional monitoring—and compared them with guideline recommendations. Expert evaluation (n = 5), readability metrics, semantic similarity (TF-IDF), and patient-centered assessments were conducted to compare personalization, innovation, clinical feasibility, evidence-based support, population applicability, clarity, and self-management guidance. RESULTS: ChatGPT recommendations aligned with at least one guideline in 50.0–64.3% of cases, highest for dysphagia (64.3%), and included general strategies such as small frequent meals, texture modification, hydration, and high-protein/high-calorie intake. ChatGPT-specific suggestions (8.3–18.2%) focused on lifestyle and behavioral interventions, including mindful eating, music therapy, and wearable diet trackers. Expert ratings indicated higher personalization (4.3/5) and innovation (4.6/5) for ChatGPT, whereas guidelines scored higher for clinical feasibility (4.7/5), evidence-based support (4.9/5), and population applicability (4.8/5). Between-group differences were statistically significant for clinical feasibility, evidence-based support, and applicability (all p < 0.01; 95% CI for mean differences: 0.62–1.12), whereas personalization showed no significant difference (p = 0.063). ChatGPT exhibited superior patient-centered performance in clarity (4.5 vs. 3.2, p = 0.004, 95% CI: 0.47–2.13) and self-management guidance (4.6 vs. 3.0, p = 0.002, 95% CI: 0.65–2.05) and demonstrated more concise, readable content (Flesch–Kincaid grade 12.9–14.2) compared with guidelines (17.9–20.5). Semantic analysis revealed moderate overlap with CSCO (≈ 0.63) and CNS (≈ 0.59), and lower similarity with ESPEN (≈ 0.47), highlighting ChatGPT’s use of patient-friendly language. Topic modeling identified three clusters: patient support and accessibility (ChatGPT), technical nutrition therapy (ESPEN/CSCO), and nutritional assessment and monitoring (CNS). CONCLUSIONS: ChatGPT provides personalized, innovative, and patient-accessible nutritional guidance for cancer-related malnutrition, complementing traditional clinical guidelines. While guidelines remain essential for evidence-based decision-making, AI tools may enhance patient education, engagement, and self-management in digital health applications. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-025-07477-0.